why springbatch job??

Spring Batch Job

Spring Batch is designed exactly for batch workloads like Pro*C migrations.

✅ Advantages:

1. Chunk-oriented processing

   • Reads N records → Processes → Commits → Moves to next chunk

   • Efficient + safe (no OOM on millions of rows)

2. Built-in Restart/Recovery

   • If job fails halfway, you don’t restart from zero, only from the last committed chunk

3. SkipPolicy / RetryPolicy

   • Mirrors Pro*C’s SQLCODE logic

   • Example:

     • SQLCODE == 0 → continue

     • SQLCODE > 0 → skip with warning

     • SQLCODE < 0 → retry or fail

4. Transaction Management

   • Auto rollback on failure in a chunk

5. Scalability

   • Parallel steps, partitioning, multi-threaded processing

6. Monitoring

   • Spring Batch provides JobRepository & metadata tables for tracking job execution history

❌ Downside:

• More setup/boilerplate than plain Java job

• Overkill for very simple, one-table jobs

🔑 When to choose which?

• Normal Java Job → Small jobs, migration utilities, POCs, rarely run jobs.

• Spring Batch → Enterprise-grade, recurring, large data sets, need monitoring, restarts, error handling, compliance, and reporting.

  
  

👉 So, if you are migrating Pro*C jobs running daily in production (millions of rows, SLA bound) → Spring Batch is the right enterprise replacement.

🔑 Side-by-Side Summary

Feature	Normal Java Job	Spring Batch Job
Simple implementation	✅ Easy	❌ More setup
Large dataset handling	❌ Risky (OOM)	✅ Chunk-based
Restartability	❌ Manual	✅ Built-in
Error handling	❌ Manual	✅ Skip/Retry API
Monitoring	❌ Custom logs	✅ Job metadata
Enterprise readiness	❌ No	✅ Yes

👉 In short:

• For one-time migration / <10K rows → Normal Java Job is fine.

• For recurring, millions of rows, SLA-bound jobs → Spring Batch is the right choice.

Can we just write a normal Java job instead of using Spring Batch?

👉 Yes, technically you can.You could simply write a Java program with JDBC (or JPA/Hibernate) that:

• Reads data from the database

• Applies business logic (like eligibility checks)

• Updates the database

• Runs on a scheduler (like Quartz, cron, or even ScheduledExecutorService)

This would work fine for small-scale, simple jobs.

But why use Spring Batch then?

Spring Batch is not just about executing jobs; it’s about handling enterprise batch processing challenges.

Here’s the comparison:

Feature	Normal Java Job	Spring Batch
Transaction Management	Manual	Built-in (chunk-based processing with rollback)
Restartability	You need to code checkpoints yourself	Built-in JobRepository stores execution metadata, resumes from last checkpoint
Scalability	Write parallel code yourself	Partitioning, parallel steps, async processing supported
Error/SQLCODE Handling	Manually catch exceptions	SkipPolicy, RetryPolicy, listeners for clean handling of SQLCODE==0, >0, <0 equivalent
Logging & Auditing	Manual logging	Automatic logging of job/step execution, job parameters
Scheduling	Quartz/Cron (manual)	Integrates with Spring Scheduler/Quartz easily
Reusability	Each job is custom-built	Configurable jobs with reusable readers/writers/processors
Complex Workflow	Hard to maintain when steps grow	Clear step/flow configuration for multi-step batch pipelines

Example

• Normal Java Job: Good for something like “read one table → update another” (simple ETL).

• Spring Batch Job: Better for “daily loan processing of millions of rows with retries, checkpoints, error handling, and scalability.”

✅ Conclusion:

• If it’s a POC or small utility job → Normal Java job is fine.

• If it’s a production-grade, enterprise batch job with large data volume, retries, monitoring, and restartability → Use Spring Batch.

🔹 When to choose Normal Java Job vs Spring Batch

Factor	Normal Java Job	Spring Batch Job
Data Size	Small (< 100k records)	Large (millions of records)
Fault Tolerance	Manual try-catch	Built-in skip/retry/checkpoints
Restartability	Must restart from scratch	Restarts from last commit point
Scheduling	Manual (cron, Quartz)	Integrated with Spring
Monitoring	Manual logs	Metrics, listeners, audit tables
Enterprise Standard	❌ Not scalable	✅ Preferred

👉 So the answer is:

• If your Pro*C job was lightweight (few rows, not business-critical) → a normal Java job might be enough.

• But since most Pro*C jobs in BFSI run in production, process millions of transactions daily, and require fault-tolerance, Spring Batch is the right migration choice.